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Hoffmann FJ, Braesemann F, Teubner T. Measuring sustainable tourism with online platform data. EPJ DATA SCIENCE 2022; 11:41. [PMID: 35873664 PMCID: PMC9289659 DOI: 10.1140/epjds/s13688-022-00354-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Accepted: 06/11/2022] [Indexed: 06/15/2023]
Abstract
UNLABELLED Sustainability in tourism is a topic of global relevance, finding multiple mentions in the United Nations Sustainable Development Goals. The complex task of balancing tourism's economic, environmental, and social effects requires detailed and up-to-date data. This paper investigates whether online platform data can be employed as an alternative data source in sustainable tourism statistics. Using a web-scraped dataset from a large online tourism platform, a sustainability label for accommodations can be predicted reasonably well with machine learning techniques. The algorithmic prediction of accommodations' sustainability using online data can provide a cost-effective and accurate measure that allows to track developments of tourism sustainability across the globe with high spatial and temporal granularity. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1140/epjds/s13688-022-00354-6.
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Affiliation(s)
- Felix J. Hoffmann
- Trust in Digital Services, Technische Universität Berlin, 10623 Berlin, Germany
| | - Fabian Braesemann
- Oxford Internet Institute, University of Oxford, OX1 3JS Oxford, UK
- Datenwissenschaftliche Gesellschaft Berlin, 10117 Berlin, Germany
| | - Timm Teubner
- Trust in Digital Services, Technische Universität Berlin, 10623 Berlin, Germany
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The Role of Informal Digital Surveillance Systems Before, During and After Infectious Disease Outbreaks: A Critical Analysis. ACTA ACUST UNITED AC 2018. [PMCID: PMC7123634 DOI: 10.1007/978-94-024-1263-5_14] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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Bhattacharyya S, Gesteland PH, Korgenski K, Bjørnstad ON, Adler FR. Cross-immunity between strains explains the dynamical pattern of paramyxoviruses. Proc Natl Acad Sci U S A 2015; 112:13396-400. [PMID: 26460003 PMCID: PMC4629340 DOI: 10.1073/pnas.1516698112] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Viral respiratory tract diseases pose serious public health problems. Our ability to predict and thus, be able to prepare for outbreaks is strained by the complex factors driving the prevalence and severity of these diseases. The abundance of diseases and transmission dynamics of strains are not only affected by external factors, such as weather, but also driven by interactions among viruses mediated by human behavior and immunity. To untangle the complex out-of-phase annual and biennial pattern of three common paramyxoviruses, Respiratory Syncytial Virus (RSV), Human Parainfluenza Virus (HPIV), and Human Metapneumovirus (hMPV), we adopt a theoretical approach that integrates ecological and immunological mechanisms of disease interactions. By estimating parameters from multiyear time series of laboratory-confirmed cases from the intermountain west region of the United States and using statistical inference, we show that models of immune-mediated interactions better explain the data than those based on ecological competition by convalescence. The strength of cross-protective immunity among viruses is correlated with their genetic distance in the phylogenetic tree of the paramyxovirus family.
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Affiliation(s)
- Samit Bhattacharyya
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA 16802; Department of Biology, University of Utah, Salt Lake City, UT 84112;
| | - Per H Gesteland
- Department of Pediatrics, School of Medicine, University of Utah, Salt Lake City, UT 84112; Department of Biomedical Informatics, University of Utah, Salt Lake City, UT 84112
| | - Kent Korgenski
- Department of Pediatrics, School of Medicine, University of Utah, Salt Lake City, UT 84112; Pediatric Clinical Program, Intermountain Healthcare, Salt Lake City, UT 84111
| | - Ottar N Bjørnstad
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA 16802; Fogarty International Center, National Institutes of Health, Bethesda, MD 20892
| | - Frederick R Adler
- Department of Biology, University of Utah, Salt Lake City, UT 84112; Department of Mathematics, University of Utah, Salt Lake City, UT 84112
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Velasco E, Agheneza T, Denecke K, Kirchner G, Eckmanns T. Social media and internet-based data in global systems for public health surveillance: a systematic review. Milbank Q 2014; 92:7-33. [PMID: 24597553 PMCID: PMC3955375 DOI: 10.1111/1468-0009.12038] [Citation(s) in RCA: 120] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Abstract
CONTEXT The exchange of health information on the Internet has been heralded as an opportunity to improve public health surveillance. In a field that has traditionally relied on an established system of mandatory and voluntary reporting of known infectious diseases by doctors and laboratories to governmental agencies, innovations in social media and so-called user-generated information could lead to faster recognition of cases of infectious disease. More direct access to such data could enable surveillance epidemiologists to detect potential public health threats such as rare, new diseases or early-level warnings for epidemics. But how useful are data from social media and the Internet, and what is the potential to enhance surveillance? The challenges of using these emerging surveillance systems for infectious disease epidemiology, including the specific resources needed, technical requirements, and acceptability to public health practitioners and policymakers, have wide-reaching implications for public health surveillance in the 21st century. METHODS This article divides public health surveillance into indicator-based surveillance and event-based surveillance and provides an overview of each. We did an exhaustive review of published articles indexed in the databases PubMed, Scopus, and Scirus between 1990 and 2011 covering contemporary event-based systems for infectious disease surveillance. FINDINGS Our literature review uncovered no event-based surveillance systems currently used in national surveillance programs. While much has been done to develop event-based surveillance, the existing systems have limitations. Accordingly, there is a need for further development of automated technologies that monitor health-related information on the Internet, especially to handle large amounts of data and to prevent information overload. The dissemination to health authorities of new information about health events is not always efficient and could be improved. No comprehensive evaluations show whether event-based surveillance systems have been integrated into actual epidemiological work during real-time health events. CONCLUSIONS The acceptability of data from the Internet and social media as a regular part of public health surveillance programs varies and is related to a circular challenge: the willingness to integrate is rooted in a lack of effectiveness studies, yet such effectiveness can be proved only through a structured evaluation of integrated systems. Issues related to changing technical and social paradigms in both individual perceptions of and interactions with personal health data, as well as social media and other data from the Internet, must be further addressed before such information can be integrated into official surveillance systems.
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Scherm H, Thomas CS, Garrett KA, Olsen JM. Meta-analysis and other approaches for synthesizing structured and unstructured data in plant pathology. ANNUAL REVIEW OF PHYTOPATHOLOGY 2014; 52:453-76. [PMID: 25001455 DOI: 10.1146/annurev-phyto-102313-050214] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
The term data deluge is used widely to describe the rapidly accelerating growth of information in the technical literature, in scientific databases, and in informal sources such as the Internet and social media. The massive volume and increased complexity of information challenge traditional methods of data analysis but at the same time provide unprecedented opportunities to test hypotheses or uncover new relationships via mining of existing databases and literature. In this review, we discuss analytical approaches that are beginning to be applied to help synthesize the vast amount of information generated by the data deluge and thus accelerate the pace of discovery in plant pathology. We begin with a review of meta-analysis as an established approach for summarizing standardized (structured) data across the literature. We then turn to examples of synthesizing more complex, unstructured data sets through a range of data-mining approaches, including the incorporation of 'omics data in epidemiological analyses. We conclude with a discussion of methodologies for leveraging information contained in novel, open-source data sets through web crawling, text mining, and social media analytics, primarily in the context of digital disease surveillance. Rapidly evolving computational resources provide platforms for integrating large and complex data sets, motivating research that will draw on new types and scales of information to address big questions.
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Affiliation(s)
- H Scherm
- Department of Plant Pathology, University of Georgia, Athens, Georgia 30602;
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Hartley DM, Nelson NP, Arthur RR, Barboza P, Collier N, Lightfoot N, Linge JP, van der Goot E, Mawudeku A, Madoff LC, Vaillant L, Walters R, Yangarber R, Mantero J, Corley CD, Brownstein JS. An overview of internet biosurveillance. Clin Microbiol Infect 2013; 19:1006-13. [PMID: 23789639 DOI: 10.1111/1469-0691.12273] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Internet biosurveillance utilizes unstructured data from diverse web-based sources to provide early warning and situational awareness of public health threats. The scope of source coverage ranges from local media in the vernacular to international media in widely read languages. Internet biosurveillance is a timely modality that is available to government and public health officials, healthcare workers, and the public and private sector, serving as a real-time complementary approach to traditional indicator-based public health disease surveillance methods. Internet biosurveillance also supports the broader activity of epidemic intelligence. This overview covers the current state of the field of Internet biosurveillance, and provides a perspective on the future of the field.
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Affiliation(s)
- D M Hartley
- Imaging Science and Information Systems Center, Georgetown University School of Medicine, Washington, DC, USA; Department of Microbiology and Immunology, Georgetown University Medical Center, Washington, DC, USA
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Nelson NP, Yang L, Reilly AR, Hardin JE, Hartley DM. Event-based internet biosurveillance: relation to epidemiological observation. Emerg Themes Epidemiol 2012; 9:4. [PMID: 22709988 PMCID: PMC3493297 DOI: 10.1186/1742-7622-9-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2011] [Accepted: 06/06/2012] [Indexed: 11/24/2022] Open
Abstract
Background The World Health Organization (WHO) collects and publishes surveillance data and statistics for select diseases, but traditional methods of gathering such data are time and labor intensive. Event-based biosurveillance, which utilizes a variety of Internet sources, complements traditional surveillance. In this study we assess the reliability of Internet biosurveillance and evaluate disease-specific alert criteria against epidemiological data. Methods We reviewed and compared WHO epidemiological data and Argus biosurveillance system data for pandemic (H1N1) 2009 (April 2009 – January 2010) from 8 regions and 122 countries to: identify reliable alert criteria among 15 Argus-defined categories; determine the degree of data correlation for disease progression; and assess timeliness of Internet information. Results Argus generated a total of 1,580 unique alerts; 5 alert categories generated statistically significant (p < 0.05) correlations with WHO case count data; the sum of these 5 categories was highly correlated with WHO case data (r = 0.81, p < 0.0001), with expected differences observed among the 8 regions. Argus reported first confirmed cases on the same day as WHO for 21 of the first 64 countries reporting cases, and 1 to 16 days (average 1.5 days) ahead of WHO for 42 of those countries. Conclusion Confirmed pandemic (H1N1) 2009 cases collected by Argus and WHO methods returned consistent results and confirmed the reliability and timeliness of Internet information. Disease-specific alert criteria provide situational awareness and may serve as proxy indicators to event progression and escalation in lieu of traditional surveillance data; alerts may identify early-warning indicators to another pandemic, preparing the public health community for disease events.
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Affiliation(s)
- Noele P Nelson
- Department of Pediatrics, Georgetown University Medical Center, Washington, DC, 20007, USA.
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Corley CD, Lancaster MJ, Brigantic RT, Chung JS, Walters RA, Arthur RR, Bruckner-Lea CJ, Calapristi A, Dowling G, Hartley DM, Kennedy S, Kircher A, Klucking S, Lee EK, McKenzie T, Nelson NP, Olsen J, Pancerella C, Quitugua TN, Reed JT, Thomas CS. Assessing the continuum of event-based biosurveillance through an operational lens. Biosecur Bioterror 2012; 10:131-41. [PMID: 22320664 DOI: 10.1089/bsp.2011.0096] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
This research follows the Updated Guidelines for Evaluating Public Health Surveillance Systems, Recommendations from the Guidelines Working Group, published by the Centers for Disease Control and Prevention nearly a decade ago. Since then, models have been developed and complex systems have evolved with a breadth of disparate data to detect or forecast chemical, biological, and radiological events that have a significant impact on the One Health landscape. How the attributes identified in 2001 relate to the new range of event-based biosurveillance technologies is unclear. This article frames the continuum of event-based biosurveillance systems (that fuse media reports from the internet), models (ie, computational that forecast disease occurrence), and constructs (ie, descriptive analytical reports) through an operational lens (ie, aspects and attributes associated with operational considerations in the development, testing, and validation of the event-based biosurveillance methods and models and their use in an operational environment). A workshop was held in 2010 to scientifically identify, develop, and vet a set of attributes for event-based biosurveillance. Subject matter experts were invited from 7 federal government agencies and 6 different academic institutions pursuing research in biosurveillance event detection. We describe 8 attribute families for the characterization of event-based biosurveillance: event, readiness, operational aspects, geographic coverage, population coverage, input data, output, and cost. Ultimately, the analyses provide a framework from which the broad scope, complexity, and relevant issues germane to event-based biosurveillance useful in an operational environment can be characterized.
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Affiliation(s)
- Courtney D Corley
- National Security Directorate, Pacific Northwest National Laboratory, Richland, WA 99352, USA.
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Thomas CS, Nelson NP, Jahn GC, Niu T, Hartley DM. Use of media and public-domain Internet sources for detection and assessment of plant health threats. EMERGING HEALTH THREATS JOURNAL 2011; 4:7157. [PMID: 24149031 PMCID: PMC3168368 DOI: 10.3402/ehtj.v4i0.7157] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/05/2011] [Revised: 06/30/2011] [Accepted: 07/26/2011] [Indexed: 12/04/2022]
Abstract
Event-based biosurveillance is a recognized approach to early warning and situational awareness of emerging health threats. In this study, we build upon previous human and animal health work to develop a new approach to plant pest and pathogen surveillance. We show that monitoring public domain electronic media for indications and warning of epidemics and associated social disruption can provide information about the emergence and progression of plant pest infestation or disease outbreak. The approach is illustrated using a case study, which describes a plant pest and pathogen epidemic in China and Vietnam from February 2006 to December 2007, and the role of ducks in contributing to zoonotic virus spread in birds and humans. This approach could be used as a complementary method to traditional plant pest and pathogen surveillance to aid global and national plant protection officials and political leaders in early detection and timely response to significant biological threats to plant health, economic vitality, and social stability. This study documents the inter-relatedness of health in human, animal, and plant populations and emphasizes the importance of plant health surveillance.
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Affiliation(s)
- Carla S. Thomas
- Division of Integrated Biodefense, Imaging Science and Information Systems, Georgetown University Medical Center, Washington, DC, USA
| | - Noele P. Nelson
- Division of Integrated Biodefense, Imaging Science and Information Systems, Georgetown University Medical Center, Washington, DC, USA
- Department of Pediatrics, Georgetown University Medical Center, Washington, DC, USA
| | - Gary C. Jahn
- Division of Integrated Biodefense, Imaging Science and Information Systems, Georgetown University Medical Center, Washington, DC, USA
- Department of Radiology, Georgetown University Medical Center, Washington, DC, USA
| | - Tianchan Niu
- Division of Integrated Biodefense, Imaging Science and Information Systems, Georgetown University Medical Center, Washington, DC, USA
- Department of Radiology, Georgetown University Medical Center, Washington, DC, USA
| | - David M. Hartley
- Division of Integrated Biodefense, Imaging Science and Information Systems, Georgetown University Medical Center, Washington, DC, USA
- Department of Radiology, Georgetown University Medical Center, Washington, DC, USA
- Department of Microbiology and Immunology, Georgetown University Medical Center, Washington, DC, USA
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